MétaCan
Menu
Retour à la cohorte
Enregistrement W2997359134

Population genomics of a timberline conifer, subalpine larch (Larix lyallii Parl.)

2019· dissertation· ceb· W2997359134 sur OpenAlexaboutno aff
Marie Vance

Notice bibliographique

RevueUVic’s Research and Learning Repository (University of Victoria) · 2019
Typedissertation
Langueceb
DomaineAgricultural and Biological Sciences
ThématiqueForest Ecology and Biodiversity Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLarchMontane ecologyGeographyPopulationForestryBiologyEcologyDemography
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Subalpine larch (Larix lyallii Parl.) has a narrow ecological niche at timberline in the Cascade Range and the Rocky Mountains of western North America. Demographic factors, including a long generation time (average 500 years) and a late arrival at sexual maturity (100-200 years), make it unlikely that this species will be able to adapt to predicted climate change. A better understanding of genetic structure and genetic diversity is necessary in order to effectively manage this species for future generations. Foliage from 62 populations of subalpine larch was collected in order to elucidate the range-wide population genomics of the species. DNA was extracted and a next-generation sequencing method, restriction site associated DNA sequencing (RAD-seq), was used to generate genome-wide single nucleotide polymorphism (SNP) marker data. Three genetically differentiated clusters were identified via principal components analysis, a discriminant analysis of principal components and Bayesian STRUCTURE analysis: the Cascade Range, the southern Rocky Mountains and the northern Rocky Mountains. A monophyletic group in the central Rocky Mountains was also identified in a dendrogram of genetic distance but this group had weak bootstrap support (49%), meaning genetic differentiation depends on relatively few genetic variants. Genetically differentiated groups should be prioritized for future management and conservation efforts. Negative values of Tajima’s D and preferred demographic scenarios generated by coalescent simulations indicated that 15 populations all have a recent history of expansion. Genetic diversity within these populations was found to be moderate (HO = 0.15 – 0.20), inbreeding coefficients were found to be high (FIS = 0.15 – 0.25) and genetic differentiation among populations was found to be high (average FST = 0.18). These results indicated that fragmentation driven by Holocene warming may have resulted in reduced effective population sizes. Smaller populations experience stronger genetic drift and an increased likelihood of inbreeding, which may hinder an adaptive response to natural selection. Still, parameter estimates for preferred demographic scenarios suggested a minimum effective population size of around 20,000 individuals, which is not considered small by most conservationists. A final study of 18 populations found local adaptation to cold temperature in the northern portion of the species range. In all seasons, populations from the northern Rocky Mountains had significantly higher cold tolerance than populations from the central Canadian Rocky Mountains and the northern Cascades. Winter cold tolerance showed strong clines associated with the frost-free period and degree days below zero. These two climate variables explained 65% of the explainable variance in phenotype when redundancy analysis models were conditioned on geography. Seven SNPs were identified that explained a significant portion of the variance in winter cold tolerance. Range-wide, additional SNPs were identified as FST outliers and/or as significantly correlated with environmental gradients, even after correcting for neutral genetic structure. Together, the results of this work indicate that dispersal, neutral evolutionary processes and natural selection have all played important roles in shaping patterns of genetic variation across the natural range of subalpine larch. All of these factors should be considered during the development of management and conservation strategies for this high-elevation conifer species.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,032
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0020,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,027
Tête enseignante GPT0,258
Écart entre enseignants0,231 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2019
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueUVic’s Research and Learning Repository (University of Victoria)Même sujetForest Ecology and Biodiversity StudiesTravaux en français237 207